Resource Type

Journal Article 232

Year

2023 32

2022 32

2021 17

2020 27

2019 29

2018 9

2017 11

2016 5

2015 4

2014 8

2013 4

2012 2

2011 5

2010 9

2009 7

2008 1

2007 3

2006 3

2005 2

2004 2

open ︾

Keywords

Deep learning 36

deep learning 15

Artificial intelligence 11

Machine learning 6

Deep mining 4

Deep neural network 4

Deep reinforcement learning 4

Autonomous driving 3

Accelerator 2

Attention 2

Big data 2

COVID-19 2

Computed tomography 2

Computer vision 2

Deep Learning 2

Deep convolutional neural network 2

Deep neural networks 2

artificial intelligence 2

computer vision 2

open ︾

Search scope:

排序： Display mode:

Development and deep-sea exploration of the Haidou-1

Frontiers of Engineering Management   Pages 546-549 doi: 10.1007/s42524-023-0260-6

Abstract: Development and deep-sea exploration of the Haidou-1

Keywords： hadal zone     autonomous and remotely-operated vehicle     integrated exploration operation     deep dive exceeding10000 meters    

HTML PDF Collect

RETRACTED ARTICLE: Using a Newton-type technique for smart meters estimation frequency of electric power

Tanveer AHMAD,Qadeer UI HASAN

Frontiers in Energy 2016, Volume 10, Issue 4,   Pages 489-489 doi: 10.1007/s11708-016-0395-9

HTML PDF Collect

Effect of harmonic distortion on electric energy meters of different metrological principles

Illia DIAHOVCHENKO, Vitalii VOLOKHIN, Victoria KUROCHKINA, Michal ŠPES, Michal KOSTEREC

Frontiers in Energy 2019, Volume 13, Issue 2,   Pages 377-385 doi: 10.1007/s11708-018-0571-1

Abstract: that the errors in energy measurements depend on the design and the algorithms used in electricity metersSuch traits lead to the discrepancies in the readings of commercial electric energy meters of different

Keywords： current     distortion     electric energy meter     harmonics     power quality    

HTML PDF Collect

DSM in an area consisting of residential, commercial and industrial load in smart grid

Balasubramaniyan SARAVANAN

Frontiers in Energy 2015, Volume 9, Issue 2,   Pages 211-216 doi: 10.1007/s11708-015-0351-0

Abstract: With the latest introduction of the demand side management (DSM) in smart grids, the power distribution units are able to modify the load schedules of the consumers. This involves a co-operative interaction of the utility and the consumers so as to achieve customer load modifications in which the customer, utility and society all are benefited. The interaction is performed with the help of the devices known as the smart meter. This paper shows the use of game theory and logical mathematical expressions in order to achieve the objectives. The objectives are to minimize the peak to average ratio (PAR) and the energy cost. The outcome of the game between supplier and customers helps to shape the load profile. The design proposed in this paper is very user-friendly and is based on simple logarithmic programming computations. In this paper, residential, commercial and industrial types of loads are taken into account. A basic 24 h load schedule along with the fluctuating prices at each hour of the day is forecasted by the supplier of the various shiftable and non-shiftable loads and then that schedule is conveyed to the user. The users are encouraged to shift their high load devices to off-peak hours which will not only reduce their electricity costs but also substantially reduce the PAR in the load demand.

Keywords： demand side management (DSM)     smart grids     peak to average ratio (PAR)     smart meters and logarithmic price    

HTML PDF Collect

Digital image correlation-based structural state detection through deep learning

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 1,   Pages 45-56 doi: 10.1007/s11709-021-0777-x

Abstract: This paper presents a new approach for automatical classification of structural state through deep learning

Keywords： structural state detection     deep learning     digital image correlation     vibration signal     steel frame    

HTML PDF Collect

Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Frontiers of Structural and Civil Engineering   Pages 994-1010 doi: 10.1007/s11709-023-0942-5

Abstract: Hence, a gated recurrent unit (GRU)-based deep learning framework is proposed herein to dynamically predicteffective decision support for moving trajectory control and serve as a foundation for the application of deep

Keywords： dynamic prediction     moving trajectory     pipe jacking     GRU     deep learning    

HTML PDF Collect

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: First, a new deep reinforcement learning (DRL) is developed, and it constructs an agent aiming at controllingSecond, a new structure of DRL is designed by combining deep deterministic policy gradient and long short-termACNN is also compared with other published machine learning (ML) and deep learning (DL) methods.

Keywords： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

HTML PDF Collect

Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 11,   Pages 930-939 doi: 10.1631/FITEE.1500125

Abstract: In this paper we propose a novel method to estimate head pose based on a deep convolutional neural network

Keywords： Head pose estimation     Deep convolutional neural network     Multiclass classification    

HTML PDF Collect

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 496-506 doi: 10.1007/s11684-021-0828-7

Abstract: In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture

Keywords： XGBoost     deep neural network     healthcare     risk prediction    

HTML PDF Collect

Stability analysis on Tingzikou gravity dam along deep-seated weak planes during earthquake

Weiping HE, Yunlong HE

Frontiers of Structural and Civil Engineering 2012, Volume 6, Issue 1,   Pages 69-75 doi: 10.1007/s11709-012-0146-x

Abstract: The stability of a gravity dam against sliding along deep-seated weak planes is a universal and importantThere is no recommended method for stability analysis of the dam on deep-seated weak planes under earthquakeis focused on searching a proper way to evaluate the seismic safety of the dam against sliding along deep-seatedweak planes and the probable failure modes of dam on deep-seated weak planes during earthquake.

Keywords： gravity dam     deep-seated weak planes     stability against sliding     earthquake    

HTML PDF Collect

Study of the Variable Load While Estimating Existing Bridge Structure

Suo Qinghui,Qian Yongjiu,Zhang Fang

Strategic Study of CAE 2004, Volume 6, Issue 5,   Pages 52-55

Abstract:

On the basis of design load in force, the revised factors of variable load used in estimating existing bridge structures are given according to the theory, which is the probability that the load used exceeds the reservice term should be equal to the probability that the load used in design exceeds the service term. The theory of time-dependent ability is adopted to evaluate the residual service life of structure and a method is adopted to revise the variable load.

Keywords： bridge structure     variable load     equal exceeding probability     time-dependent ability     re-service life    

HTML PDF Collect

Survey on deep learning for pulmonary medical imaging

Jiechao Ma, Yang Song, Xi Tian, Yiting Hua, Rongguo Zhang, Jianlin Wu

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 450-469 doi: 10.1007/s11684-019-0726-4

Abstract: As a promising method in artificial intelligence, deep learning has been proven successful in severalWith medical imaging becoming an important part of disease screening and diagnosis, deep learning-basedDeep learning has been widely applied in medical imaging for improved image analysis.This paper reviews the major deep learning techniques in this time of rapid evolution and summarizesLastly, the application of deep learning techniques to the medical image and an analysis of their future

Keywords： deep learning     neural networks     pulmonary medical image     survey    

HTML PDF Collect

Advanced finite element analysis of a complex deep excavation case history in Shanghai

Yuepeng DONG, Harvey BURD, Guy HOULSBY, Yongmao HOU

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 1,   Pages 93-100 doi: 10.1007/s11709-014-0232-3

Abstract: North Square Shopping Center of the Shanghai South Railway Station is a large scale complex top-down deepconcrete floor slabs and beams, 4) the complex construction sequences, and 5) the shape effect of the deep

Keywords： advanced finite element analysis     deep excavations     case history     small-strain stiffness    

HTML PDF Collect

Theoretical and technological exploration of deep

Heping XIE, Yang JU, Shihua REN, Feng GAO, Jianzhong LIU, Yan ZHU

Frontiers in Energy 2019, Volume 13, Issue 4,   Pages 603-611 doi: 10.1007/s11708-019-0643-x

Abstract: Mining industries worldwide have inevitably resorted to exploiting resources from the deep undergroundTo exploit deep resources in the future, the concept of mining must be reconsidered and innovative newThe limits of mining depth need to be broken to acquire deep-coal resources in an environmentally friendlyFirst, this paper systematically explains deep fluidized coal mining.Finally, this paper presents a strategic roadmap for deep fluidized coal mining.

Keywords： coal resource     deep in situ     fluidized mining     theoretical system     key technologies     strategic roadmap    

HTML PDF Collect

Title Author Date Type Operation

Development and deep-sea exploration of the Haidou-1

Journal Article

RETRACTED ARTICLE: Using a Newton-type technique for smart meters estimation frequency of electric power

Tanveer AHMAD,Qadeer UI HASAN

Journal Article

Effect of harmonic distortion on electric energy meters of different metrological principles

Illia DIAHOVCHENKO, Vitalii VOLOKHIN, Victoria KUROCHKINA, Michal ŠPES, Michal KOSTEREC

Journal Article

DSM in an area consisting of residential, commercial and industrial load in smart grid

Balasubramaniyan SARAVANAN

Journal Article

Intellectual control—A goal exceeding the century - speech on the Fourteenth Conference IFAC

Song Jian

Journal Article

Digital image correlation-based structural state detection through deep learning

Journal Article

Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

Journal Article

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Journal Article

Stability analysis on Tingzikou gravity dam along deep-seated weak planes during earthquake

Weiping HE, Yunlong HE

Journal Article

Study of the Variable Load While Estimating Existing Bridge Structure

Suo Qinghui,Qian Yongjiu,Zhang Fang

Journal Article

Survey on deep learning for pulmonary medical imaging

Jiechao Ma, Yang Song, Xi Tian, Yiting Hua, Rongguo Zhang, Jianlin Wu

Journal Article

Advanced finite element analysis of a complex deep excavation case history in Shanghai

Yuepeng DONG, Harvey BURD, Guy HOULSBY, Yongmao HOU

Journal Article

Theoretical and technological exploration of deep

Heping XIE, Yang JU, Shihua REN, Feng GAO, Jianzhong LIU, Yan ZHU

Journal Article